AI-900T00 Microsoft Azure AI Fundamentals (UT-Microsoft-AI-900T00)


Course Description

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.

Course Outline

1 - Get started with AI on Azure

  • Understand machine learning
  • Understand anomaly detection
  • Understand computer vision
  • Understand natural language processing
  • Understand knowledge mining
  • Challenges and risks with AI
  • Understand Responsible AI

2 - Use Automated Machine Learning in Azure Machine Learning

  • What is machine learning?
  • What is Azure Machine Learning studio?
  • What is Azure Automated Machine Learning?
  • Understand the AutoML process

3 - Create a regression model with Azure Machine Learning designer

  • Identify regression machine learning scenarios
  • What is Azure Machine Learning?
  • What is Azure Machine Learning designer?
  • Understand steps for regression

4 - Create a classification model with Azure Machine Learning designer

  • Identify classification machine learning scenarios
  • What is Azure Machine Learning?
  • What is Azure Machine Learning designer?
  • Understand steps for classification

5 - Create a clustering model with Azure Machine Learning designer

  • Identify clustering machine learning scenarios
  • What is Azure Machine Learning?
  • What is Azure Machine Learning designer?
  • Understand steps for clustering

6 - Analyze images with the Computer Vision service

  • Get started with image analysis on Azure

7 - Classify images with the Custom Vision service

  • Understand classification
  • Get started with image classification on Azure

8 - Detect objects in images with the Custom Vision service

  • What is object detection?
  • Get started with object detection on Azure

9 - Detect and analyze faces with the Face service

  • Get started with Face analysis on Azure

10 - Read text with the Computer Vision service

  • Get started with the Read API on Azure

11 - Analyze receipts with the Form Recognizer service

  • Get started with receipt analysis on Azure

12 - Analyze text with the Language service

  • Get started with text analysis

13 - Recognize and synthesize speech

  • Get started with speech on Azure

14 - Translate text and speech

  • Get started with translation in Azure

15 - Create a language model with Conversational Language Understanding

  • Getting started with Conversational Language Understanding

16 - Build a bot with the Language Service and Azure Bot Service

  • Get started with the Language service and Azure Bot Service

Course Prerequisites

Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically:

  • Experience using computers and the internet.
  • Interest in use cases for AI applications and machine learning models.
  • A willingness to learn through hands-on exp...

Course Information

Length: 1 day

Format: Lecture and Lab

Delivery Method: Virtual

Max. Capacity: 16



Schedule

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Who Should Attend

The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful.